An information provision system according to residents’ indoor comfort preferences for energy conservation

Abstract

A Home Energy Management System is a key component to achieve energy efficiency on the residential side in a Smart City. The proposed system includes two processes: one to collect environmental and physical data using networked sensors, and the other to submit web-based questionnaires for calculating Predicted Mean Vote values, which is an indicator of personal comfort in homes. Another part of this system selects information obtained from the collected data every 30 min to encourage appropriate changes in personal behavior, so as to provide the preferred level of comfort. Information is generated for each resident’s comfort range. To test its applicability, the system was installed in two test households for two weeks in summer and in winter. In the first week, environmental and physical data were collected. This created a benchmark for electricity consumption. In the second week, information was provided, which was used to customize the comfort level for each person. The evaluation showed that the system contributed to a reduction in electricity consumption by approximately 13.3 %, and an increase in indoor comfort by approximately 65.5 % during both summer and winter, when electricity consumption peaks and indoor comfort is at its lowest.